22 Average consumption in the country during the years 2000-2010
amounted Libya 21,211,206 MWh, consumption 14,522,025 MWh lowest and highest value of the consumption at 31,680,704 MWh. The total amount of
consumption in 2000-2010 amounted to 233,323,266 MWh.
4.2.1.4 Statistic descriptive of population
Population from year 2000-2010 in the State of the lowest Libya reach 5,231,189 person and 6,355,112 person achieve complete biggest population on
Libyan state as the below table. Table 4.6
Description of Population from 2000-2010 N
Valid 11
Missing Mean
5,785,868 Median
5,769,709 Mode
5,231,189
a
Std. Deviation 383,063
Minimum 5,231,189
Maximum 6,355,112
Sum 63,644,551
Population in the country of Libya reached 5,785,868 person. the entire population of the year 2000-2010 reached number 63,644,551 person
4.2.2 Goodness-of-Fit Measures
Table of summary statistics for stationary R-square, R-square, root mean square error, mean absolute percentage error, mean absolute error, maximum
absolute percentage error, maximum absolute error, and normalized Bayesian Information Criterion. The Normalized Bayesian Information Criterion, as a
general measure of the overall fit of a model that attempts to account for model complexity. It is a score based upon the mean square error and includes a penalty
for the number of parameters in the model and the length of the series. The penalty removes the advantage of models with more parameters, making the
statistic easy to compare across different models for the same series Norušis, 2007.
commit to user
23 Table 4.7
Model Fit Statistic Model
Stationary R- squared
R-squared RMSE
MAPE Production-Model_1
.580 .991
884,1431.741 1.763
Generated-Model_2 .580
.991 57,4491.991
1.763 Consumption-
Model_3 -1.757E-16
.958 1,217,524.605 3.815
Population-Model_4 0.000
1.000 4,947.405
.071 Continue Table 4.7
Model MAE
MaxAPE MaxAE
Normalized BIC
Production-Model_1 6,021,407.853
4.308 19,004,280.541 32.426
Generated-Model_2 391,254.571
4.308 1,234,846.040
26.958 Consumption-
Model_3 783,931.280
10.868 3,015,625.100
28.255 Population-Model_4
4,272.438 .125
7,839.250 17.273
Stationary R - squared. A measure that compares the stationary part of the model to a simple average. Variables that have a negative value that is
consumption, which means that the model under consideration is worse than the base line model. While the variable production costs, generated, population have a
positive value means that the model under consideration is better than the basic model.
R - Squared. Estimates of the proportion of the total variation in the series described by the model. This step is very useful when the series is stationary. All
variables have a positive value means that the model under consideration is better than the basic model.
RMSE. Root Mean Square Error. The square root of the mean square error. A measure of how much the series varies depending on the level of its
prediction models, expressed in the same units as the dependent series. RMSE of all the variables with the highest consumption variable 1,217,524.605 value and a
low of population variable with a value of 4,947.405 MAPE. Absolute Percentage Error means. A measure of how much the
series varies depending on the level of its prediction models. It does not depend on the units used and can therefore be used to compare series with different units.
commit to user
24 As for who has the highest MAPE lowest in the population variable with a value
of 0.071 MAE. Mean absolute error. Measures how much the series varies from its
level prediction models. MAE is the highest on the production variable value and the lowest 6,021,407.853 population variable with a value of 4,272.438
MaxAPE. Maximum Absolute Percentage Error. The largest estimated error, expressed as a percentage. MaxAPE highest in the variable value
consumption by 10.868 and the population with the lowest value of 0.125. MaxAE. Maximum Absolute Error. The largest estimated error. MaxAE
highest in variable production abaout 19,004,280.541 and the lowest values occurring in the population variable with a value of 7,839,250.
Normalized BIC. Normalized Bayesian Information Criterion. General measure overall model fit that tries to explain the complexity of the model.
Normalized BIC variables that have high production is a variable with a value of 32,426 and the lowest values occur in the population variable with a value of 17.
273.
4.2.3 Result Analysis ARIMA Model Parameters by SPSS
